Project? ?Summary/Abstract Millions? ?of? ?Americans? ?receive? ?evidence-based? ?counseling? ?for? ?substance? ?use? ?problems? ?each? ?year.? ?Many evidence-based? ?treatments? ?for? ?substance? ?abuse? ?are? ??talk? ?based?? ?therapies,? ?such? ?as? ?motivational? ?interviewing (MI),? ?but? ?the? ?existing? ?research-based? ?methodology? ?for? ?evaluating? ?counseling? ?quality? ?is? ?to? ?record? ?sessions? ?and use? ?human? ?rating? ?teams? ?to? ?evaluate? ?them.? ?However,? ?using? ?humans? ?as? ?the? ?assessment? ?tool? ?via? ?behavioral coding? ?is? ?prohibitive? ?in? ?cost? ?and? ?time,? ?can? ?be? ?error? ?prone,? ?and? ?is? ?virtually? ?never? ?used? ?in? ?the? ?real? ?world. Technology? ?is? ?needed? ?that? ?can? ?analyze? ?the? ?speech? ?patterns? ?and? ?spoken? ?language? ?of? ?counseling? ?sessions, provide? ?automatic? ?and? ?intuitive? ?quality? ?scores,? ?and? ?summarize? ?these? ?in? ?actionable? ?feedback.? ?Rapid, performance-based? ?quality? ?metrics? ?could? ?support? ?training,? ?ongoing? ?supervision,? ?and? ?quality? ?assurance? ?for millions? ?of? ?evidence-based? ?counseling? ?sessions? ?for? ?substance? ?abuse? ?each? ?year. Lyssn.io?? ?is? ?a? ?start-up? ?targeting? ?the? ?development? ?of? ?implementation-focused? ?technology? ?to? ?support evidence-based? ?counseling.? ?? ?Our? ?goal? ?is? ?to? ?develop? ?innovative? ?health? ?technology? ?solutions? ?that? ?are? ?objective, scalable,? ?and? ?cost? ?efficient.? ??Lyssn.io?? ?includes? ?expertise? ?in? ?speech? ?signal? ?processing,? ?machine? ?learning, user-centered? ?design,? ?software? ?engineering,? ?and? ?clinical? ?expertise? ?in? ?evidence-based? ?counseling.? ?Previous NIH-funded? ?research? ?laid? ?a? ?computational? ?foundation? ?for? ?generating? ?MI? ?quality? ?metrics? ?from? ?speech? ?and language? ?features? ?in? ?MI? ?sessions,? ?and? ?led? ?to? ?a? ?prototype? ?of? ?a? ?clinical? ?software? ?support? ?tool,? ?the? ?Counselor Observer? ?Ratings? ?Expert? ?for? ?MI? ?(CORE-MI). The? ?current? ?Fast-Track? ?SBIR? ?proposal? ?includes? ?Phase? ?I,? ?which? ?will? ?focus? ?on? ?understanding? ?clinical workflows,? ?assessing? ?usability,? ?and? ?initial? ?validation? ?of? ?machine? ?learning? ?of? ?MI? ?fidelity? ?measures? ?in? ?the? ?opioid treatment? ?program? ?at? ?Evergreen? ?Treatment? ?Services? ?(ETS)? ?clinic? ?in? ?Seattle,? ?WA.? ?Phase? ?II? ?will? ?focus? ?on? ?robust validation? ?of? ?the? ?speech? ?and? ?language? ?technologies? ?underlying? ?the? ?CORE-MI? ?tool,? ?and? ?development? ?of? ?scalable supervision? ?protocols? ?that? ?integrate? ?CORE-MI? ?supported? ?feedback? ?for? ?counselors.? ?Finally,? ?we? ?will? ?conduct? ?a quasi-experimental? ?evaluation? ?of? ?CORE-MI? ?supported? ?supervision? ?and? ?training? ?at? ?a? ?second? ?ETS? ?clinic? ?in? ?the Puget? ?Sound,? ?focusing? ?on? ?acceptability,? ?usability,? ?and? ?adoption,? ?the? ?impact? ?on? ?supervision,? ?improved? ?MI? ?fidelity and? ?preliminary? ?evidence? ?of? ?increased? ?client? ?retention.? ?? ?The? ?successful? ?execution? ?of? ?this? ?project? ?will? ?break? ?the reliance? ?on? ?human? ?judgment? ?for? ?providing? ?performance-based? ?feedback? ?to? ?MI? ?and? ?will? ?massively? ?expand? ?the capacity? ?to? ?train,? ?supervise,? ?and? ?provide? ?quality? ?assurance? ?in? ?MI? ?for? ?substance? ?abuse.